发表机构
University of Pittsburgh（匹兹堡大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究广告视觉唤起感官问题，引入感官广告数据集和分类任务，提出SenseScore评估指标，介绍感官广告生成任务及SAGA多智能体框架，为感官感知视觉说服奠定基础。
AI 中文摘要
感官广告通过视觉线索唤起人类感官，使受众能够在脑海中模拟体验并增强说服力。尽管近期人工智能在生成和理解创意及有说服力的内容方面应用增多，但广告如何通过视觉唤起感官仍未得到充分探索。本文首次对理解、评估和生成感官广告进行研究，引入感官广告数据集并定义感官分类任务以对语言模型进行基准测试，还提出自动评估指标SenseScore，最后介绍感官广告生成任务并提出多智能体框架SAGA，为感官感知视觉说服奠定基础。
英文摘要
Sensory advertising evokes human senses through visual cues, enabling audiences to mentally simulate experiences and increasing persuasive impact. Despite the recent increase in using AI in generating and understanding creative and persuasive content, how advertisements visually evoke sensations remains largely unexplored. In this work, we introduce the first study of understanding, evaluating, and generating sensory ads. We introduce the Sensory Ad dataset, and define sensation classification tasks (SenseClass) to benchmark LLMs and MLLMs. We further propose SenseScore, an automated evaluation metric for sensation evocation achieving strong agreement with human judgments. Finally, we introduce the Sensory Ad Generation (SenseGen) task and propose SAGA, a multi-agent framework that improves message image alignment, sensory evocation, and persuasion. Our work establishes a foundation for sensory-aware visual persuasion.
